Protection of parallel transmission lines including inter-circuit faults using Naïve Bayes classifier

Abstract

Parallel transmission lines are difficult to protect due to mutual coupling between circuits. This paper proposes a Naïve Bayes classifier (NBC) based fault detection and classification technique for protection of parallel transmission line involving inter-circuit faults. NBC is a good classification tool for larger data sets as the training process takes less time with greater accuracy. Input given to the fault detection module is the fundamental components of three phase current signals of both circuits. Input given to the fault phase identification and fault classification module is the fundamental component of three phase current signals and zero sequence currents of both the circuits. Seven separate classifiers are designed for fault phase identification for A1, B1, C1, A2, B2, C2 and G. From fault phase identification module faults are classified. Accuracy of the proposed method is 100% for fault detection and 99.99% for classification of fault from all the tested fault cases. Response time of the proposed method is within 10 ms for all the fault cases studied